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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Performance-Oriented Partitioning for Task Scheduling of Parallel Reconfigurable Architectures
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Performance-Oriented Partitioning for Task Scheduling of Parallel Reconfigurable Architectures

机译：面向性能的分区，用于并行可重配置架构的任务调度

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摘要

Dynamic reconfiguration is important for reconfigurable platforms. Parallel reconfigurable computing (PRC) architecture consists of multiple dynamic reconfigurable computing (DRC) units. Thus, for a circuit to be implemented on a parallel reconfiguration system, it needs to be partitioned such that each sub-circuit can be executed to the DRC units in a PRC system. For high performance, this paper proposes a greedy algorithm that maximizes data parallelism for task scheduling of parallel reconfigurable architectures with unlimited resources. The proposed algorithm generates an optimal solution in polynomial time O(n), where n is the total number of the tasks. After obtaining a depth optimal solution, we reduce the resources without decreasing performance by the duplication packing operations whose time complexity is O(n). To demonstrate the performance of the proposed algorithm, we not only compare the existing methods with standard benchmarks but also implement on physical systems, like DSP, FIR, and JPEG. The experimental results show that the proposed algorithms satisfy the requirements of the performance-oriented systems with limited resources. Hence, we have sufficient reason to believe that the runtime must be reasonable for general applications.
机译：动态重新配置对于可重新配置的平台很重要。并行可重构计算（PRC）架构由多个动态可重构计算（DRC）单元组成。因此，对于要在并行重配置系统上实现的电路，需要对其进行分区，以使每个子电路都可以执行到PRC系统中的DRC单元。为了实现高性能，本文提出了一种贪婪算法，该算法可以最大化数据并行性，以实现资源无限的并行可重配置体系结构的任务调度。所提出的算法在多项式时间O（n）中生成最优解，其中n是任务总数。在获得深度最优解后，我们通过时间复杂度为O（n）的重复打包操作减少资源而不降低性能。为了证明所提出算法的性能，我们不仅将现有方法与标准基准进行比较，而且在诸如DSP，FIR和JPEG的物理系统上实现。实验结果表明，所提出的算法满足了资源有限，面向性能的系统的需求。因此，我们有充分的理由相信运行时对于常规应用程序必须是合理的。

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